Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour models

Analytical and Quantitative Cytology and Histology

Volumn 26, Issue 6, 2004, Pages 331-340

  Glotsos, Dimitris ^a   Spyridonos, Panagiota ^a   Cavouras, Dionisis ^b   Ravazoula, Panagiota ^c   Dadioti, Petroula Arampantoni ^d   Nikiforidis, George ^a  

^a UNIVERSITY OF PATRAS   (Greece)

^b UNIVERSITY OF WEST ATTICA   (Greece)

^c University Hospital   (Greece)

^d Metaxas Anticancer Hospital   (Greece)

Author keywords

Active contour; Automated segmentation; Computer assisted diagnosis; Support vector machine clustering

Indexed keywords

EOSIN; HEMATOXYLIN;

ALGORITHM; ARTICLE; ASTROCYTOMA; AUTOMATED SEGMENTATION; BLADDER CANCER; CANCER CLASSIFICATION; CELL NUCLEUS; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED MICROSCOPY; DIAGNOSTIC ACCURACY; HUMAN; IMAGE ANALYSIS; LABORATORY AUTOMATION; METHODOLOGY; MICROSCOPY; PRIORITY JOURNAL; STAINING; SUPPORT VECTOR MACHINE CLUSTERING ALGORITHM; TISSUE SECTION; VALIDATION PROCESS;

ALGORITHMS; ASTROCYTOMA; AUTOMATION; BIOPSY; CELL NUCLEUS; EOSINE YELLOWISH-(YS); HEMATOXYLIN; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGE PROCESSING, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; STAINING AND LABELING; URINARY BLADDER NEOPLASMS;

SERPENTES;

EID: 11144312356     PISSN: 08846812     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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